Edge detecting method and edge detecting device which detects edges for each individual primary color and employs individual color weighting coefficients

ABSTRACT

An edge detecting method and an edge detecting device detecting from a picture element group which is changing rapidly as compared with its surroundings an edge from within image data in which each picture element is composed of independent N numbers of dark and light data R, G, and B respectively, by calculating N sets of coefficients Wr, Wg, Wb corresponding to N numbers of dark and light data R, G, B respectively, and each picture element is judged whether it is an edge or not depending upon N numbers of dark and light data R, G, B and N sets of coefficients Wr, Wg, Wb.

This is a continuation of co-pending application Ser. No. 08/518,233filed on Aug. 23, 1995.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an edge detecting method and an edgedetecting device and conducts the edge detecting processing which playsa basic role especially on the image processing, and can be suitablyapplied to such as the special effect processing in the video productionof television and motion pictures and the element recognition processingfrom the camera image in the FA (factory automation).

2. Description of the Related Art

Heretofore, the edge detection has been a process to find the part wherethe picture element value is rapidly changing between dark and lightimages. And since normally sudden changes occur on the outline of theobject, the contour of the object can be extracted from the pictorialimage depending on the result of edge detection. Therefore, edgedetection has been widely utilized as the most basic processing forobtaining information from the image on the object existing in thatimage.

In the color images, since dark and light image exist in every primarycolor (e.g., red, green, and blue), heretofore the edge detection hasbeen conducted on each primary color and if the edge is detected on anycolor, that picture element is regarded as an edge of the color image.This will be explained referring to the image shown in FIG. 1A. Thisimage is a round object shown in FIG. 1B which is placed in front of thebackground having a horizontal line shown in FIG. 1C.

In the case of this image, the dark and light image of three primarycolors, red, green, and blue become like FIG. 2A, 2B, and 2Crespectively. For example, in the case of red, the picture element valueof the inside of area 1 shown by oblique lines is "1.0" and the pictureelement value of the inside of the remaining area 2 is "0". The samewill be applied to green and blue. If the edge is detected on each darkand light image, since the edge on the part where the sudden changeoccurs, i.e., only the place where the picture element value changesfrom "1.0" to "0" can be obtained as the edge, edges like FIG. 3A, 3B,and 3C corresponding to FIG. 2A, 2B, and 2C will be obtained. If theedge is detected in any one of the colors, red, green, or blue, itspicture element is considered as an edge, and the edge which can beultimately obtained will be like FIG. 3D by combining these edges.

However, since the edge obtained as described above contains ahorizontal line 4 in the background and a vertical line 5 of the insideof a circle besides a contour 3 of the circle to be aimed originally,recognition of the real contour by means of the computer becomes verydifficult. Like this example, the problem that unnecessary parts aredetected as edges occurs in the case where there are patterns or colorsand changes in lightness exist in the object and background.

Since it is common that there exist patterns and colors and changes inlightness on the object to be aimed for extraction from the imagebackground or from within an image, it is practically impossible toextract the contour from the optional image by means of the conventionaldevice, and in practice the contour extraction by the computer has beenconducted only under limited condition, such as in the case where thebackground is painted with a uniform color.

Various improvements have heretofore been developed to alleviate theseproblems based on experience. For example, when the edge was detected ineither primary color, that picture element was not only regarded as anedge but the method has been modified taking great account of lightnesschanges. However, since the application of dark and light image of eachprimary color is fixed in advance, these cannot be applied to imageswhich did not follow the law of experience, and they were insufficientfor practical use as the edge detection accuracy.

SUMMARY OF THE INVENTION

In view of the foregoing, an object of the present invention is toprovide an edge detecting method and edge detecting device capable ofimproving the accuracy of edge detection and extracting the contourcorrectly in the general image.

The foregoing object and other objects of this invention have beenachieved by the provision of an edge detecting method for detecting apicture element group changing rapidly as compared with its surroundingsas an edge E(x,y) from within image data in which each picture elementis composed of N numbers of independent dark and light data R(x,y),G(x,y), B(x,y) respectively. This is accomplished by a method comprisinga coefficient calculating step SP1 for calculating N sets ofcoefficients Wr(x,y), Wg(x,y), Wb(x,y) corresponding to N numbers ofdark and light data R(x,y), G(x,y), B(x,y) respectively, and judgingsteps SP2, SP3, SP4 for judging whether each picture element is the edgeE(x,y) or not based on N numbers of dark and light data R(x,y), G(x,y),B(x,y) and N sets of coefficients Wr(x,y), Wg(x,y), Wb(x,y).

Furthermore, according to the present invention, an edge detectingdevice 10 for detecting a picture element group changing rapidly ascompared with its surroundings from within image data in which eachpicture element is composed of N numbers of independent dark and lightdata 11, 12, 13 respectively, is comprised of a coefficient calculatingmeans 14 for calculating N sets of coefficients Wr, Wg, Wb correspondingto N numbers of dark and light data 11, 12, 13 respectively, and ajudging means 16 for judging whether each picture element is the edge ornot based on N numbers of dark and light data 11, 12, 13 and N sets ofcoefficients Wr, Wg, Wb.

In the case of detecting the group of picture elements which is changingrapidly as compared with its surroundings as the edge E(x,y) from withinimage data in which picture elements is composed of N numbers ofindependent dark and light data R(x,y), G(x,y), B(x,y), since N sets ofcoefficients Wr(x,y), Wg(x,y), Wb(x,y) corresponding to N numbers ofdark and light data R(x,y), G(x,y), B(x,y) respectively will becalculated and each picture element will be judged as to where it is theedge or not based on N numbers of dark and light data R(x,y), G(x,y),B(x,y) and N sets of coefficients Wr(x,y), Wg(x,y), Wb(x,y), the edgedetection accuracy can be improved and the contour can be correctlyextracted even in the general image.

The nature, principle and utility of the invention will become moreapparent from the following detailed description when read inconjunction with the accompanying drawings in which like parts aredesignated by like reference numerals or characters.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings:

FIGS. 1A to 1C are brief linear diagrams showing the color image to beused for explanation of edge detection;

FIGS. 2A to 2C are brief linear diagrams showing the color image ofFIGS. 1A to 1C upon decomposing into dark and light images of eachprimary color;

FIGS. 3A to 3D are brief linear diagrams showing an output of which eachdark and light image is independently edge detected and its combinedoutput;

FIG. 4 is a flow chart showing an edge detection processing procedure inone embodiment of the edge detecting method according to the presentinvention;

FIG. 5 is a block diagram showing the construction of the firstembodiment of the edge detecting device according to the presentinvention;

FIGS. 6A and 6B are brief linear diagrams explaining the edge detectingoperation of color images of FIGS. 1A to 1C according to the edgedetecting method of the present invention;

FIGS. 7A to 7C are brief linear diagrams explaining the fundamentals ofa coefficient calculating method of the present invention;

FIG. 8 is a block diagram showing the construction of the secondembodiment of the edge detecting device according to the presentinvention; and

FIGS. 9A and 9B are brief linear diagrams showing the Sobel filter fordetecting the edge of special directions being used in the edgedetecting device of FIG. 8.

DETAILED DESCRIPTION OF THE EMBODIMENT

Preferred embodiments of the present invention will be described withreference to the accompanying drawings:

(1) The First Embodiment

FIG. 4 shows an edge detecting processing procedure to be conducted bythe computer of the image processing device applied to the edgedetecting method according to the present invention. At step SP1 of thisedge detecting processing procedure, the color image data which will bethe object of processing and the most suitable weight coefficient forthe edge detection will be inputted. The color image data is made up ofthree primary colors, dark and a light image of red, green, and blue,respectively R(x,y), G(x,y), B(x,y) will be inputted. Also, weightcoefficients on red, green, and blue will be Wr(x,y), Wg(x,y), Wb(x,y)respectively. Since values of these weight coefficients differ in eachpixel of the image, i.e., each x, y, the optimal parameter for edgedetection can be determined in every small part in the image at thatplace.

For example, in the case where it is known that an upper half of thescreen is trees and a lower half is the surface of the water of a lake,the most suitable weight coefficient for green color may be given in theupper part of the screen and the most suitable weight coefficient forblue line color may be given at the lower part. These characteristics ofan image can be obtained generally as the condition at the time ofphotographing. Also, the user can give them to the computer afterwards.The computer calculates an appropriate coefficient depending upon thecharacteristic of the image given. This becomes the input of the stepSP1. The coefficient determination of the image shown in FIGS. 1A to 1Cwill be described in detail below. If the whole screen can give theequal weight coefficient, the fixed number WR may be given in place ofthe weight coefficient Wr(x,y) (also the other primary colors) and inthat case, the storage for the weight coefficient can be reduced.

Furthermore, at step SP2, the inner product at each picture element willbe calculated based on dark and light images of three primary colorsR(x,y), G(x,y), and B(x,y) and weight coefficients Wr(x,y), Wg(x,y),Wb(x,y) from the following equation:

    I(x,y)=Wr(x,y)R(x,y)+Wg(x,y)G(x,y)+Wb(x,y)B(x,y)           (1)

Here, I(x,y) is the inner product value. The previous color image wasthree dimensional data having three values in each picture element.However, this step SP2 converts this to the one dimensional innerproduct value I(x,y). According to the calculation of this step SP2, theedge detection sensitive only to the contour is possible and its effectwill be described later referring to examples. And since the output ofthe step SP2 has one value on each picture element, this can be regardedas the normal dark and light images.

The step SP3 and step SP4 are steps for detecting the edge consideringthe inner product value I(x,y) as dark and light images. The step SP3 isthe processing for calculating the rate of change in the x-direction andy-direction of the inner product value I(x,y). The step SP41 is theprocessing to search the direction where the change of the inner productvalue I(x,y) is most rapid, the step SP42 is the processing to obtainthe quantity of change G(x,y) in that direction, and the step SP43 isthe processing for binary coding the quantity of change G(x,y) obtainedin utilizing the prefixed threshold value Gth. The result of binarycoding is obtained as the edge image E(x,y).

This series of processings is based upon the well known edge detectionalgorithm of the Canny system for an edge detection method for dark andlight images in which the value of each picture element is onedimensional, and there are many other known methods. These methods areintroduced in detail, such as in the typical textbook written by Jain"Fundamentals of Digital Image Processing". And these methods can beused in this embodiment at steps SP3 and SP4.

Furthermore, FIG. 5 shows one embodiment of the edge detecting deviceaccording to the present invention. The image data that will be theobject for processing is held as dark and light images 11 (R), 12 (G),13 (B) of each primary color red, green, and blue. The coefficientcalculating unit 14 obtains the most suitable coefficient to detect theedge from the image data, and outputs them as coefficients Wr, Wg, Wbrelating to red, green, blue respectively. The inner product calculatingunit 15 obtains products of red part and coefficient Wr, green part andcoefficient Wg, and blue part and coefficient Wb in the picture elementvalue S1 respectively and by adding these, calculates the inner productvalue I. This is equivalent to the calculation of step SP2 of the edgedetection processing procedure of FIG. 4.

The resulting inner product value I is inputted to the judging unit 16and judged whether each picture element is the edge or not. This judgingunit 16 conducts the processing of steps SP3 and SP4 of the edgedetection processing procedure of FIG. 4. As a result, concerning eachpicture element, the judging unit 16 outputs "1" if it is the edge, andif it is not, outputs the judgment signal E to become "0". And if theseare stored in the arrangement of the same size as the former image, theresult of edge detection is obtained as a binary image 17 so that onlythe edge is "1".

At this point, according to the present invention, as an effect of theinner product calculation using the weight coefficient, if the imagedata of FIG. 1A is inputted, dark and light images 11, 12, 13 of FIG. 5become FIG. 2A, 2B, 2C respectively. At this point, if the coefficientcalculating unit 14 calculates coefficients as Wr=1.0, Wg=1.0, Wb=0.0using the method to be described later, the output E of the innerproduct calculating unit 15 become as shown in FIG. 6A.

More specifically, since in an area 20 of FIG. 6A, only red pictureelement value is "1.0" and green and blue picture element values are"0", the inner product value I to be obtained by the equation (1) is"1". Moreover, since in an area 23 all picture element values are "1.0"but Cb=0, the inner product value become "2.0" by the equation (1). Ifthe similar calculation is conducted on the remaining areas 21, 22, itis apparent that the inner product value of the inside of the circularobject is "2.0" as shown in FIG. 6A and the inner product value in thebackground is "1.0".

More specifically, the inner product value I does not change eitherinside of the round object or inside of the background but changes onlyat the border of the round object and background. Thus, if the changingpart of inner product value I is detected, the outline of the objectaimed can be easily edge detected as shown in FIG. 6B. Extra edges asshown in FIG. 3B which could not be avoided by the conventional methoddo not occur. Accordingly, in the edge detecting device 10 of thisembodiment, an appropriate edge detection can be conducted not dependingon the pictorial image because the coefficient calculating unit 14obtains appropriate coefficients Wr, Wg, Wb corresponding to the imagedata.

The computing method of coefficients Wr, Wg, Wb in the coefficientcalculating unit 14 will be shown below. FIG. 7A shows the distributionof image data of FIG. 1A in the coordinate system with three primarycolors the coordinate axis (hereinafter referred to as color space). Thepoint 30 shows the part of cyan color in the background and the point 31shows the red part in the background. More specifically, colors formingthe background exist inside of an area 32 in the color space. Similarly,the white part of the round object corresponds to the point 33 and theyellow part corresponds to the point 34 respectively, and as a whole,colors in the round object exist inside of an area 35 in the colorspace. If the vector CV perpendicularly intersecting these two areas isobtained in the color space and makes the vector CV factor as the outputof the coefficient calculating unit 14, highly accurate edge detectioncan be conducted.

According to this embodiment, since the vector CV which is (red, green,blue)=(1, 1, 0) intersects the area 32 and area 35 at right angles, itis alright to let (Wr, Wg, Wb)=(1, 1, 0). The inner product computationat the inner product computing unit 15 based on coefficients Wr, Wg, andWb thus obtained means obtaining the size of element along the vector CVwithin colors. In FIG. 7, the inner product of the vector CV and coloris equal to that of projecting a solid object in the direction of theblue axis of (FIG. 7B) and to observe this from the side along thevector CV and measure the distance from the original point (FIG. 7C.

As it is clear from FIG. 7C, colors existed in the area 32 in the formercolor space are all projected to the point of the inner product value"1.0" and on the other hand, colors in the area 35 are projected all tothe point of the inner product value "2.0". More specifically, the innerproduct value of vector CV and color reacts only to the color changebetween the background and the object regardless of color change in thebackground area and color change of the inside of the round object.Thus, it is apparent that utilizing this inner product value, the objectcan be separated accurately from the background.

There are cases where no vector which intersects completely both thebackground area and the object area at right angles exists in some imagedata. However, an efficient edge detection having less noise as comparedwith the conventional method is possible if it is so arranged that thevector intersects these areas at right angles and the inner productvalue of the background and the object area is different and is selectedto make the coefficient as an output of the coefficient calculating unit14.

According to the foregoing construction, in the case of detecting thepicture element group which is rapidly changing as compared with thesurroundings from within the image data in which the picture elementsare composed of dark and light images R, G, B of three primary colorsrespectively as edges, since coefficients Wr, Wg, Wb for 3 primarycolors corresponding to each of dark and light images of 3 primarycolors are computed and each picture element is judged whether it is theedge or not based on dark and light images of 3 primary colors R, G, Band coefficients Wr, Wg, Wb, the accuracy in edge detection can beimproved and contours can be correctly extracted in the general image.Furthermore, according to the foregoing construction, although dark andlight images R, G, B exist as 3 numbers, the edge detection may beconducted only on the inner product value I and thus, only one judgingunit 16 is necessary and the quantity of hardware can be reduced ascompared with the past.

(2) The Second Embodiment

The second embodiment is a device which combines the edge detectingmethod and edge detecting device described above in FIG. 4 and FIG. 5with a known edge detecting method in order to achieve higher accuracyin a further improved detecting method. More specifically, an edgedetecting device 40 shown in FIG. 8 in which corresponding parts of FIG.5 are given the same reference numerals is a device invented in order tocope with the very difficult case where a clear edge cannot be detectedeven utilizing the edge detection device 10 of FIG. 5.

The difference between the edge detecting device 10 of FIG. 5 and thisembodiment is that the judging unit 41 judges the edge in utilizing theestimated value 42 in the edge direction in addition to an inner productvalue I. The estimated value 42 in the edge direction is made up inadvance depending upon a knowledge concerning the approximate positionsof objects in the image. In the case where the judging unit 41 detectsthe part on which the inner product value I changes rapidly, itfunctions in order to detect with priority to the direction change,i.e., the edge, using the estimated value 42 in the edge direction.

With regard to the edge detecting method which reacts strongly tospecial direction changes, there is a method to use the Sobel filter asshown in FIGS. 9A and 9B for example. More specifically, when thisfilter of FIG. 9A is applied to the image, the change in the horizontaldirection, i.e., vertical edge, is strongly detected. In the samemanner, when the filter of FIG. 9B is applied to the image, the verticalchange, i.e., the edge extending horizontally is detected strongly.

Furthermore, there are many other filters known as the compasscalculator and the edge in the specific direction can be detected. If itis combined with these known methods, edge detection which react sharplyto the desired outline, and the outline extraction with higher accuracycan be obtained.

According to the foregoing construction, since the estimated value inthe edge direction is obtained utilizing the general edge detectingmethod and each picture element is judged whether it is edge or notdepending on the estimated value in the edge direction, the accuracy inedge detection can be further improved and the outline can be correctlyextracted in the general image.

(3) Other Embodiments

Furthermore, the embodiment described above has dealt with the case ofdetecting edges on the image data composed of dark and light image ofthree primary colors, i.e., red, green, and blue. However, the imagedata is not only limited to the above but also it is widely applicableto the case of detecting the edge in the image data composed of multipledark and light data such as complimentary color line dark and lightimages.

According to the present invention as described above, since N sets ofcoefficients corresponding to N numbers of dark and light datarespectively are calculated and each picture element is judged whetherit is an edge or not in the case of detecting the rapidly changingpicture element group as compared with its surroundings as the edge fromwithin image data in which a picture element is composed of N numbers ofindependent dark and light data, an edge detecting method and edgedetecting device capable of improving the edge detection accuracy andcapable of extracting the outline in the general image correctly can berealized. With this arrangement, the extraction of the outline of anobject by the computer becomes possible even in a state where it wasdifficult in the past and automation and the operational assistance bythe computer in wider range will be possible.

While there has been described in connection with the preferredembodiments of the invention, it will be obvious to those skilled in theart that various changes and modifications may be aimed, therefore, tocover in the appended claims all such changes and modifications as fallwithin the true spirit and scope of the invention.

What is claimed is:
 1. An edge detecting method for detecting a group ofpicture elements which is changing rapidly as compared with itssurroundings as an edge from within an image data in which each pictureelement is composed of N numbers of independent dark and light data ofprimary colors, respectively, the group of elements together forming animage make up of pixels, comprising:a weight coefficient generating stepfor generating N sets of weight coefficients corresponding to said Nnumbers of dark and light data, respectively, the value of each weightcoefficient being different for each pixel of the image; and a judgingstep for judging whether said each picture element is an edge or notbased on said N numbers of dark and light data of each primary color andsaid N sets of weight coefficients; wherein said judging stepincludes:an inner product calculating step for calculating an innerproduct which is the product sum of said N sets of weight coefficientsand said N numbers of dark and light data, and a determining step fordetermining whether said each picture element is an edge or not based onan output of said inner product calculating step; and further whereinthe determining step comprises the steps of:(a) calculating a rate ofchange of the inner product in the x and y directions; and (b) for allpicture elements:(i) searching for a direction wherein the rate ofchange of the inner product value is sudden; (ii) calculating thequantity of change in the direction wherein the rate of change of theinner product value is determined to be sudden; and (iii) binary codingthe result of step (b)(ii) as an edge image E(x,y).
 2. An edge detectingdevice for detecting a group of picture elements which is changingrapidly as compared with its surroundings as an edge from within animage data in which the picture element is composed of N numbers ofindependent dark and light data of each primary color, respectively, thegroup together forming an image made up of pixels, comprising:weightcoefficient generating means for generating N sets of weightcoefficients corresponding to said N numbers of dark and light data,respectively, the value of each weight coefficient being different foreach pixel of the image; and judging means for judging whether said eachpicture element is an edge or not in accordance with said N numbers ofdark and light data of each primary color and said N sets of weightcoefficients; wherein said judging means comprisesinner productcalculating means for calculating an inner product which is the productsum of said N sets of weight coefficient and said N numbers of dark andlight data, and determining means for determining whether said eachpicture element is an edge or not based on the output of said innerproduct calculating means; and further wherein the determining meanscomprises:(a) means for calculating a rate of change of the innerproduct in the x and y directions for all picture elements; (b) meansfor searching for a direction wherein the rate of change of the innerproduct value is sudden; (c) means for calculating the quantity ofchange in the direction wherein the rate of change of the inner productvalue is determined to be sudden; and (d) means for binary coding theresults of the means for calculating as an edge image E(x,y).
 3. An edgedetecting method for detecting a group of picture elements which ischanging rapidly as compared with its surroundings as an edge fromwithin an image data in which each picture element is composed of Nnumbers of independent dark and light data of primary colors,respectively, the group of elements together forming an image made up ofpixels, comprising:a weight coefficient generating step for generating Nsets of weight coefficients corresponding to said N numbers of dark andlight data, respectively, the value of each weight coefficient beingdifferent for each pixel of the image; an inner product calculating stepfor calculating an inner product which is the product sum of said N setsof weight coefficients and said N numbers of dark and light data; and adetermining step for determining whether said each picture element is anedge or not based on an output of said inner product calculatingstep;wherein said each picture element is judged to be an edge or notbased on said N numbers of dark and light data of each primary color andsaid N sets of weight coefficients; wherein said determining stepincludes:(a) calculating a rate of change of the inner product in the xand y directions; and (b) for all picture elements:(i) searching for adirection wherein the rate of change of the inner product value issudden; (ii) calculating the quantity of change in the direction whereinthe rate of change of the inner product value is determined to besudden; and (iii) binary coding the result of step (b)(ii) as an edgeimage E(x,y).
 4. An edge detecting device for detecting a group ofpicture elements which is changing rapidly as compared with itssurroundings as an edge from within an image data in which the pictureelement is composed of N numbers of independent dark and light data ofeach primary color, respectively, the group together forming an imagemade up of pixels, comprising:weight coefficient generating means forgenerating N sets of weight coefficients corresponding to said N numbersof dark and light data, respectively, the value of each weightcoefficient being different for each pixel of the image; inner productcalculating means for calculating an inner product which is the productsum of said N sets of weight coefficient and said N numbers of dark andlight data; and determining means for determining whether said eachpicture element is an edge or not based on the output of said innerproduct calculating means;wherein said each picture element is judged tobe an edge or not in accordance with said N numbers of dark and lightdata of each primary color and said N sets of weight coefficients; andfurther wherein the determining means comprises:(a) means forcalculating a rate of change of the inner product in the x and ydirections for all picture elements; (b) means for searching for adirection wherein the rate of change of the inner product value issudden; (c) means for calculating the quantity of change in thedirection wherein the rate of change of the inner product value isdetermined to be sudden; and (d) means for binary coding the results ofthe means for calculating as an edge image E(x,y).
 5. An edge detectingapparatus for detecting a group of picture elements which is changingrapidly as compared with its surroundings as an edge from within animage data in which the picture element is composed of N numbers ofindependent dark and light data of each primary color, respectively, thegroup together forming an image made up of pixels, comprising:a weightcoefficient generating unit for generating N sets of weight coefficientscorresponding to said N numbers of dark and light data, respectively,the value of each weight coefficient being different for each pixel ofthe image; and a judging unit for judging whether said each pictureelement is an edge or not in accordance with said N numbers of dark andlight data of each primary color and said N sets of weight coefficients;wherein said judging unit includes:an inner product calculating unit forcalculating an inner product which is the product sum of said N sets ofweight coefficient and said N numbers of dark and light data, and adetermining unit for determining whether said each picture element is anedge or not based on the output of said inner product calculating unit;and further wherein the determining unit includes:(a) a firstcalculating unit for calculating a rate of change of the inner productin the x and y directions for all picture elements; (b) a searching unitfor searching for a direction wherein the rate of change of the innerproduct value is sudden; (c) a second calculating unit for calculatingthe quantity of change in the direction wherein the rate of change ofthe inner product value is determined to be sudden; and (d) a binarycoding unit for binary coding the results of the second calculating unitas an edge image E(x,y).
 6. An edge detecting apparatus for detecting agroup of picture elements which is changing rapidly as compared with itssurroundings as an edge from within an image data in which the pictureelement is composed of N numbers of independent dark and light data ofeach primary color, respectively, the group together forming an imagemade up of pixels, comprising:a weight coefficient generating unit forgenerating N sets of weight coefficients corresponding to said N numbersof dark and light data, respectively, the value of each weightcoefficient being different for each pixel of the image; an innerproduct calculating unit for calculating an inner product which is theproduct sum of said N sets of weight coefficient and said N numbers ofdark and light data; and a determining unit for determining whether saideach picture element is an edge or not based on the output of said innerproduct calculating unit;wherein said each picture element is judged tobe an edge or not in accordance with said N numbers of dark and lightdata of each primary color and said N sets of weight coefficients; andfurther wherein the determining unit includes:(a) a first calculatingunit for calculating a rate of change of the inner product in the x andy directions for all picture elements; (b) a searching unit forsearching for a direction wherein the rate of change of the innerproduct value is sudden; (c) a second calculating unit for calculatingthe quantity of change in the direction wherein the rate of change ofthe inner product value is determined to be sudden; and (d) a binarycoding unit for binary coding the results of the second calculating unitas an edge image E(x,y).
 7. An edge detecting method for detecting agroup of picture elements which is changing rapidly as compared with itssurroundings as an edge from within an image data in which each pictureelement is composed of N numbers of independent dark and light data ofprimary colors, respectively, the group of elements together forming animage made up of pixels, comprising the steps of:weight coefficientgenerating step for generating N sets of weight coefficientscorresponding to said N numbers of dark and light data, respectively;inner-product calculating step for calculating a sum of products witheach of the sets of weight coefficients and the dark and light datawhich correspond to each of the sets; and determining step fordetermining whether said each picture element is an edge or not based onan output of said product calculating step;wherein the determining stepincludes the steps of:(a) calculating a rate of change of the innerproduct in the x and y directions; and (b) for all picture elements:(i)searching for a direction wherein the rate of change of the innerproduct value is sudden; (ii) calculating the quantity of change in thedirection wherein the rate of change of the inner product value isdetermined to be sudden; and (iii) binary coding the result of step(b)(ii) as an edge image E(x,y) wherein the value of each weightcoefficient differs for each pixel of the image.
 8. An edge detectingmethod for detecting a group of picture elements which is changingrapidly as compared with its surroundings as an edge from within animage data in which each picture element is composed of N numbers ofindependent dark and light data of primary colors, respectively, thegroup of elements together forming an image made up of pixels,comprising the steps of:weight coefficient generating step forgenerating N sets of weight coefficients corresponding to said N numbersof dark and light data, respectively; inner-product calculating step forcalculating a sum of products with each of the sets of weightcoefficients and the dark and light data which correspond to each of thesets; and determining step for determining whether said each pictureelement is an edge or not based on an output of said product calculatingstep;wherein the determining step includes the steps of:(a) calculatinga rate of change of the inner product in the x and y directions; and (b)for all picture elements:(i) searching for a direction wherein the rateof change of the inner product value is sudden; (ii) calculating thequantity of change in the direction wherein the rate of change of theinner product value is determined to be sudden; and (iii) binary codingthe result of step (b)(ii) as an edge image E(x,y).
 9. An edge detectingapparatus for detecting a group of picture elements which is changingrapidly as compared with its surroundings as an edge from within animage data in which each picture element is composed of N numbers ofindependent dark and light data of primary colors, respectively, thegroup of elements together forming an image made up of pixels,comprising:a weight coefficient generating unit for generating N sets ofweight coefficients corresponding to said N numbers of dark and lightdata, respectively; an inner-product calculating unit for calculating asum of products with each of the sets of weight coefficients and thedark and light data which correspond to each of the sets; and adetermining unit for determining whether said each picture element is anedge or not based on an output of said product calculating unit; whereinthe determining unit includes:(a) a first calculating unit forcalculating a rate of change of the inner product in the x and ydirections; and (b) for all picture elements:(i) a searching unit forsearching for a direction wherein the rate of change of the innerproduct value is sudden; (ii) a second calculating unit for calculatingthe quantity of change in the direction wherein the rate of change ofthe inner product value is determined to be sudden; and (iii) a binarycoding unit for binary coding the result of the second calculating unitas an edge image E(x,y) wherein the value of each weight coefficientdiffers for each pixel of the image.
 10. An edge detecting apparatus fordetecting a group of picture elements which is changing rapidly ascompared with its surroundings as an edge from within an image data inwhich each picture element is composed of N numbers of independent darkand light data of primary colors, respectively, the group of elementstogether forming an image made up of pixels, comprising:a weightcoefficient generating unit for generating N sets of weight coefficientscorresponding to said N numbers of dark and light data, respectively; aninner-product calculating unit for calculating a sum of products witheach of the sets of weight coefficients and the dark and light datawhich correspond to each of the sets; and a determining unit fordetermining whether said each picture element is an edge or not based onan output of said product calculating unit;wherein the determining unitincludes:(a) a first calculating unit for calculating a rate of changeof the inner product in the x and y directions; and (b) for all pictureelements:(i) a searching unit for searching for a direction wherein therate of change of the inner product value is sudden; (ii) a secondcalculating unit for calculating the quantity of change in the directionwherein the rate of change of the inner product value is determined tobe sudden; and (iii) a binary coding unit for binary coding the resultof the second calculating unit as an edge image E(x,y).